1 Data1: Consumer feelings toward wine

1.1 Missing values

Pattern of missing values

Figure 1.1: Pattern of missing values

1.2 Consumer feelings toward wine

Consumer feelings toward wine and wine consumption

Figure 1.2: Consumer feelings toward wine and wine consumption

2 Influence of brand on wine enjoyment

2.1 Round 1

2.2 Round 2

2.3 Round 3

3 Desired wine feature

This will help us to understand for which brand which particular attribute is playing a major role in the higher or lower wine enjoyment score.

3.1 Round 1

3.2 Round 2

3.3 Round 3

4 Chi square tests

4.1 Brand and Enjoyment

4.1.1 Round 1

## 
##  Pearson's Chi-squared test
## 
## data:  table(round1a$brand1, round1a$enjoy1)
## X-squared = 26.037, df = 16, p-value = 0.05351

4.1.2 Round 2

## 
##  Pearson's Chi-squared test
## 
## data:  table(round2a$brand2, round2a$enjoy2)
## X-squared = 19.103, df = 16, p-value = 0.2634

4.1.3 Round 3

## 
##  Pearson's Chi-squared test
## 
## data:  table(round3a$brand3, round3a$enjoy3)
## X-squared = 4.4085, df = 16, p-value = 0.998

4.2 Enjoy and Re-drink

4.2.1 Round 1

## 
##  Pearson's Chi-squared test
## 
## data:  table(round1a$enjoy1, round1a$drink1)
## X-squared = 35.057, df = 4, p-value = 4.523e-07

4.2.2 Round 2

## 
##  Pearson's Chi-squared test
## 
## data:  table(round2a$enjoy2, round2a$drink2)
## X-squared = 46.986, df = 4, p-value = 1.535e-09

4.2.3 Round 3

## 
##  Pearson's Chi-squared test
## 
## data:  table(round3a$enjoy3, round3a$drink3)
## X-squared = 49.129, df = 4, p-value = 5.489e-10

5 Correlation Matrix

Correlation Matrix

Figure 5.1: Correlation Matrix

6 Regression Model

6.1 Influence of wine chemical on wine enjoyment

7 Profile descriptives

## Rows: 15
## Columns: 11
## $ id       <dbl> 8, 10, 13, 2, 1, 3, 7, 6, 11, 15, 5, 14, 4, 12, 9
## $ age      <dbl> 34, 73, 51, 48, 38, 35, 51, 55, 57, 33, 45, 40, 26, 62, 23
## $ drinkout <chr> "Once a week", "More than once a week", "Once a week", "Less…
## $ spendout <chr> "$25 to less than $35", "$45 to less than $60", "Less than $…
## $ drinkhm  <chr> "More than once a week", "More than once a week", "Once a we…
## $ spendhm  <chr> "$15 to less than $25", "$15 to less than $25", "$15 to less…
## $ sex      <chr> "Female", "Female", "Male", "Female", "Male", "Male", "Male"…
## $ marital  <chr> "Single (never married)", "Other", "Single (never married)",…
## $ edu      <chr> "College graduate (bachelor’s degree or equivalent)", "Colle…
## $ ethnic   <chr> "Caucasian or White", "Latino or Hispanic", "Caucasian or Wh…
## $ income   <chr> "$50,000 to less than $75,001", "$150,000 or more", "$150,00…

7.1 Wine drinking frequency

7.2 Money spend on wine

Table 7.1: Data summary
Name profiled
Number of rows 15
Number of columns 11
_______________________
Column type frequency:
character 9
numeric 2
________________________
Group variables None

Variable type: character

skim_variable n_missing complete_rate min max empty n_unique whitespace
drinkout 0 1 11 26 0 5 0
spendout 0 1 13 20 0 4 0
drinkhm 0 1 11 26 0 4 0
spendhm 0 1 13 20 0 4 0
sex 0 1 4 6 0 2 0
marital 0 1 5 22 0 4 0
edu 0 1 12 50 0 3 0
ethnic 0 1 5 25 0 5 0
income 0 1 16 29 0 9 0

Variable type: numeric

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
id 0 1 8.00 4.47 1 4.5 8 11.5 15 ▇▇▇▇▇
age 0 1 44.73 13.84 23 34.5 45 53.0 73 ▆▇▇▆▂